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Record W2161129439 · doi:10.1144/1467-787302-044

Dispersion of gold in stream sediments in the Sungai Kuli region, Sabah, Malaysia

2003· article· en· W2161129439 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeochemistry Exploration Environment Analysis · 2003
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDispersion (optics)GeographyGeologyArchaeologyHydrology (agriculture)Environmental scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

The distribution of Au has been investigated under tropical rainforest conditions in an Au-rich tributary of the Sungai Kuamut, Sabah, Malaysia. Paired high- and low-energy sediment samples were collected, before disturbance by logging, from gravel and cobble sites on bars and riffles. Gold content of five size fractions finer than 212 μm was determined by fire-assay atomic absorption spectrometry (FA-AAS). Use of a bulk leach cyanidation (BLC) procedure for Au was also tested. A strong, but extremely erratic, Au anomaly is present in the sand-size fractions. The highest Au values are found in gravel environments and concentrations decrease with decreasing grain size to a minimum in the −53 μm fraction. To maintain anomaly contrast while minimizing the chance of missing the erratic Au anomalies, use of the −105 μm fraction is recommended for stream sediment exploration surveys in the region. Because of the abundance and low Au content of the −53 μm fraction, increased erosion and additional inputs of this fraction into the stream after logging activity could significantly dilute the Au anomaly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.203
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it